azure.ai.formrecognizer.DocumentAnalysisClient.yml

### YamlMime:PythonClass
uid: azure.ai.formrecognizer.DocumentAnalysisClient
name: DocumentAnalysisClient
fullName: azure.ai.formrecognizer.DocumentAnalysisClient
module: azure.ai.formrecognizer
inheritances:
- azure.ai.formrecognizer._form_base_client.FormRecognizerClientBase
summary: 'DocumentAnalysisClient analyzes information from documents and images, and
  classifies documents.

  It is the interface to use for analyzing with prebuilt models (receipts, business
  cards,

  invoices, identity documents, among others), analyzing layout from documents, analyzing
  general

  document types, and analyzing custom documents with built models (to see a full
  list of models

  supported by the service, see: [https://aka.ms/azsdk/formrecognizer/models](https://aka.ms/azsdk/formrecognizer/models)).
  It provides different

  methods based on inputs from a URL and inputs from a stream.


  > [!NOTE]

  > DocumentAnalysisClient should be used with API versions

  >

  > 2022-08-31 and up. To use API versions <=v2.1, instantiate a FormRecognizerClient.

  >


  New in version 2022-08-31: The *DocumentAnalysisClient* and its client methods.'
constructor:
  syntax: 'DocumentAnalysisClient(endpoint: str, credential: AzureKeyCredential |
    TokenCredential, **kwargs: Any)'
  parameters:
  - name: endpoint
    description: 'Supported Cognitive Services endpoints (protocol and hostname,

      for example: [https://westus2.api.cognitive.microsoft.com](https://westus2.api.cognitive.microsoft.com)).'
    isRequired: true
    types:
    - <xref:str>
  - name: credential
    description: 'Credentials needed for the client to connect to Azure.

      This is an instance of AzureKeyCredential if using an API key or a token

      credential from <xref:azure.identity>.'
    isRequired: true
    types:
    - <xref:azure.core.credentials.AzureKeyCredential>
    - <xref:azure.core.credentials.TokenCredential>
  - name: api_version
    description: 'The API version of the service to use for requests. It defaults
      to the latest service version.

      Setting to an older version may result in reduced feature compatibility. To
      use API versions

      <=v2.1, instantiate a FormRecognizerClient.'
    types:
    - <xref:str>
    - <xref:azure.ai.formrecognizer.DocumentAnalysisApiVersion>
examples:
- "Creating the DocumentAnalysisClient with an endpoint and API key.<!--[!code-python[Main](les\\\
  v3.2_and_later\\sample_authentication.py )]-->\n\n<!-- literal_block {\"ids\": [],\
  \ \"classes\": [], \"names\": [], \"dupnames\": [], \"backrefs\": [], \"source\"\
  : \"C:\\\\hostedtoolcache\\\\windows\\\\Python\\\\3.11.5\\\\x64\\\\Lib\\\\site-packages\\\
  \\py2docfx\\\\dist_temp\\\\5\\\\azure-ai-formrecognizer-3.3.0\\\\samples\\\\v3.2_and_later\\\
  \\sample_authentication.py\", \"xml:space\": \"preserve\", \"force\": false, \"\
  language\": \"python\", \"highlight_args\": {\"linenostart\": 1}, \"linenos\": false}\
  \ -->\n\n````python\n\n   from azure.core.credentials import AzureKeyCredential\n\
  \   from azure.ai.formrecognizer import DocumentAnalysisClient\n\n   endpoint =\
  \ os.environ[\"AZURE_FORM_RECOGNIZER_ENDPOINT\"]\n   key = os.environ[\"AZURE_FORM_RECOGNIZER_KEY\"\
  ]\n\n   document_analysis_client = DocumentAnalysisClient(endpoint, AzureKeyCredential(key))\n\
  \n   ````\n\nCreating the DocumentAnalysisClient with a token credential.<!--[!code-python[Main](les\\\
  v3.2_and_later\\sample_authentication.py )]-->\n\n<!-- literal_block {\"ids\": [],\
  \ \"classes\": [], \"names\": [], \"dupnames\": [], \"backrefs\": [], \"source\"\
  : \"C:\\\\hostedtoolcache\\\\windows\\\\Python\\\\3.11.5\\\\x64\\\\Lib\\\\site-packages\\\
  \\py2docfx\\\\dist_temp\\\\5\\\\azure-ai-formrecognizer-3.3.0\\\\samples\\\\v3.2_and_later\\\
  \\sample_authentication.py\", \"xml:space\": \"preserve\", \"force\": false, \"\
  language\": \"python\", \"highlight_args\": {\"linenostart\": 1}, \"linenos\": false}\
  \ -->\n\n````python\n\n   \"\"\"DefaultAzureCredential will use the values from\
  \ these environment\n   variables: AZURE_CLIENT_ID, AZURE_TENANT_ID, AZURE_CLIENT_SECRET\n\
  \   \"\"\"\n   from azure.ai.formrecognizer import DocumentAnalysisClient\n   from\
  \ azure.identity import DefaultAzureCredential\n\n   endpoint = os.environ[\"AZURE_FORM_RECOGNIZER_ENDPOINT\"\
  ]\n   credential = DefaultAzureCredential()\n\n   document_analysis_client = DocumentAnalysisClient(endpoint,\
  \ credential)\n\n   ````\n"
methods:
- uid: azure.ai.formrecognizer.DocumentAnalysisClient.begin_analyze_document
  name: begin_analyze_document
  summary: 'Analyze field text and semantic values from a given document.


    New in version 2023-07-31: The *features* keyword argument.'
  signature: 'begin_analyze_document(model_id: str, document: bytes | IO[bytes], **kwargs:
    Any) -> LROPoller[AnalyzeResult]'
  parameters:
  - name: model_id
    description: 'A unique model identifier can be passed in as a string.

      Use this to specify the custom model ID or prebuilt model ID. Prebuilt model
      IDs supported

      can be found here: [https://aka.ms/azsdk/formrecognizer/models](https://aka.ms/azsdk/formrecognizer/models)'
    isRequired: true
    types:
    - <xref:str>
  - name: document
    description: 'File stream or bytes. For service supported file types,

      see: [https://aka.ms/azsdk/formrecognizer/supportedfiles](https://aka.ms/azsdk/formrecognizer/supportedfiles).'
    isRequired: true
    types:
    - <xref:bytes>
    - <xref:typing.IO>[<xref:bytes>]
  - name: pages
    description: 'Custom page numbers for multi-page documents(PDF/TIFF). Input the
      page numbers

      and/or ranges of pages you want to get in the result. For a range of pages,
      use a hyphen, like

      *pages="1-3, 5-6"*. Separate each page number or range with a comma.'
    types:
    - <xref:str>
  - name: locale
    description: 'Locale hint of the input document.

      See supported locales here: [https://aka.ms/azsdk/formrecognizer/supportedlocales](https://aka.ms/azsdk/formrecognizer/supportedlocales).'
    types:
    - <xref:str>
  - name: features
    description: Document analysis features to enable.
    types:
    - <xref:list>[<xref:str>]
  return:
    description: 'An instance of an LROPoller. Call *result()* on the poller

      object to return a <xref:azure.ai.formrecognizer.AnalyzeResult>.'
    types:
    - <xref:azure.core.polling.LROPoller>[<xref:azure.ai.formrecognizer.AnalyzeResult>]
  exceptions:
  - type: azure.core.exceptions.HttpResponseError
  examples:
  - "Analyze an invoice. For more samples see the *samples* folder.<!--[!code-python[Main](les\\\
    v3.2_and_later\\sample_analyze_invoices.py )]-->\n\n<!-- literal_block {\"ids\"\
    : [], \"classes\": [], \"names\": [], \"dupnames\": [], \"backrefs\": [], \"source\"\
    : \"C:\\\\hostedtoolcache\\\\windows\\\\Python\\\\3.11.5\\\\x64\\\\Lib\\\\site-packages\\\
    \\py2docfx\\\\dist_temp\\\\5\\\\azure-ai-formrecognizer-3.3.0\\\\samples\\\\v3.2_and_later\\\
    \\sample_analyze_invoices.py\", \"xml:space\": \"preserve\", \"force\": false,\
    \ \"language\": \"python\", \"highlight_args\": {\"linenostart\": 1}, \"linenos\"\
    : false} -->\n\n````python\n\n   from azure.core.credentials import AzureKeyCredential\n\
    \   from azure.ai.formrecognizer import DocumentAnalysisClient\n\n   endpoint\
    \ = os.environ[\"AZURE_FORM_RECOGNIZER_ENDPOINT\"]\n   key = os.environ[\"AZURE_FORM_RECOGNIZER_KEY\"\
    ]\n\n   document_analysis_client = DocumentAnalysisClient(\n       endpoint=endpoint,\
    \ credential=AzureKeyCredential(key)\n   )\n   with open(path_to_sample_documents,\
    \ \"rb\") as f:\n       poller = document_analysis_client.begin_analyze_document(\n\
    \           \"prebuilt-invoice\", document=f, locale=\"en-US\"\n       )\n   invoices\
    \ = poller.result()\n\n   for idx, invoice in enumerate(invoices.documents):\n\
    \       print(f\"--------Analyzing invoice #{idx + 1}--------\")\n       vendor_name\
    \ = invoice.fields.get(\"VendorName\")\n       if vendor_name:\n           print(\n\
    \               f\"Vendor Name: {vendor_name.value} has confidence: {vendor_name.confidence}\"\
    \n           )\n       vendor_address = invoice.fields.get(\"VendorAddress\")\n\
    \       if vendor_address:\n           print(\n               f\"Vendor Address:\
    \ {vendor_address.value} has confidence: {vendor_address.confidence}\"\n     \
    \      )\n       vendor_address_recipient = invoice.fields.get(\"VendorAddressRecipient\"\
    )\n       if vendor_address_recipient:\n           print(\n               f\"\
    Vendor Address Recipient: {vendor_address_recipient.value} has confidence: {vendor_address_recipient.confidence}\"\
    \n           )\n       customer_name = invoice.fields.get(\"CustomerName\")\n\
    \       if customer_name:\n           print(\n               f\"Customer Name:\
    \ {customer_name.value} has confidence: {customer_name.confidence}\"\n       \
    \    )\n       customer_id = invoice.fields.get(\"CustomerId\")\n       if customer_id:\n\
    \           print(\n               f\"Customer Id: {customer_id.value} has confidence:\
    \ {customer_id.confidence}\"\n           )\n       customer_address = invoice.fields.get(\"\
    CustomerAddress\")\n       if customer_address:\n           print(\n         \
    \      f\"Customer Address: {customer_address.value} has confidence: {customer_address.confidence}\"\
    \n           )\n       customer_address_recipient = invoice.fields.get(\"CustomerAddressRecipient\"\
    )\n       if customer_address_recipient:\n           print(\n               f\"\
    Customer Address Recipient: {customer_address_recipient.value} has confidence:\
    \ {customer_address_recipient.confidence}\"\n           )\n       invoice_id =\
    \ invoice.fields.get(\"InvoiceId\")\n       if invoice_id:\n           print(\n\
    \               f\"Invoice Id: {invoice_id.value} has confidence: {invoice_id.confidence}\"\
    \n           )\n       invoice_date = invoice.fields.get(\"InvoiceDate\")\n  \
    \     if invoice_date:\n           print(\n               f\"Invoice Date: {invoice_date.value}\
    \ has confidence: {invoice_date.confidence}\"\n           )\n       invoice_total\
    \ = invoice.fields.get(\"InvoiceTotal\")\n       if invoice_total:\n         \
    \  print(\n               f\"Invoice Total: {invoice_total.value} has confidence:\
    \ {invoice_total.confidence}\"\n           )\n       due_date = invoice.fields.get(\"\
    DueDate\")\n       if due_date:\n           print(f\"Due Date: {due_date.value}\
    \ has confidence: {due_date.confidence}\")\n       purchase_order = invoice.fields.get(\"\
    PurchaseOrder\")\n       if purchase_order:\n           print(\n             \
    \  f\"Purchase Order: {purchase_order.value} has confidence: {purchase_order.confidence}\"\
    \n           )\n       billing_address = invoice.fields.get(\"BillingAddress\"\
    )\n       if billing_address:\n           print(\n               f\"Billing Address:\
    \ {billing_address.value} has confidence: {billing_address.confidence}\"\n   \
    \        )\n       billing_address_recipient = invoice.fields.get(\"BillingAddressRecipient\"\
    )\n       if billing_address_recipient:\n           print(\n               f\"\
    Billing Address Recipient: {billing_address_recipient.value} has confidence: {billing_address_recipient.confidence}\"\
    \n           )\n       shipping_address = invoice.fields.get(\"ShippingAddress\"\
    )\n       if shipping_address:\n           print(\n               f\"Shipping\
    \ Address: {shipping_address.value} has confidence: {shipping_address.confidence}\"\
    \n           )\n       shipping_address_recipient = invoice.fields.get(\"ShippingAddressRecipient\"\
    )\n       if shipping_address_recipient:\n           print(\n               f\"\
    Shipping Address Recipient: {shipping_address_recipient.value} has confidence:\
    \ {shipping_address_recipient.confidence}\"\n           )\n       print(\"Invoice\
    \ items:\")\n       for idx, item in enumerate(invoice.fields.get(\"Items\").value):\n\
    \           print(f\"...Item #{idx + 1}\")\n           item_description = item.value.get(\"\
    Description\")\n           if item_description:\n               print(\n     \
    \              f\"......Description: {item_description.value} has confidence:\
    \ {item_description.confidence}\"\n               )\n           item_quantity\
    \ = item.value.get(\"Quantity\")\n           if item_quantity:\n             \
    \  print(\n                   f\"......Quantity: {item_quantity.value} has confidence:\
    \ {item_quantity.confidence}\"\n               )\n           unit = item.value.get(\"\
    Unit\")\n           if unit:\n               print(f\"......Unit: {unit.value}\
    \ has confidence: {unit.confidence}\")\n           unit_price = item.value.get(\"\
    UnitPrice\")\n           if unit_price:\n               unit_price_code = unit_price.value.code\
    \ if unit_price.value.code else \"\"\n               print(\n                \
    \   f\"......Unit Price: {unit_price.value}{unit_price_code} has confidence: {unit_price.confidence}\"\
    \n               )\n           product_code = item.value.get(\"ProductCode\")\n\
    \           if product_code:\n               print(\n                   f\"......Product\
    \ Code: {product_code.value} has confidence: {product_code.confidence}\"\n   \
    \            )\n           item_date = item.value.get(\"Date\")\n           if\
    \ item_date:\n               print(\n                   f\"......Date: {item_date.value}\
    \ has confidence: {item_date.confidence}\"\n               )\n           tax =\
    \ item.value.get(\"Tax\")\n           if tax:\n               print(f\"......Tax:\
    \ {tax.value} has confidence: {tax.confidence}\")\n           amount = item.value.get(\"\
    Amount\")\n           if amount:\n               print(\n                   f\"\
    ......Amount: {amount.value} has confidence: {amount.confidence}\"\n         \
    \      )\n       subtotal = invoice.fields.get(\"SubTotal\")\n       if subtotal:\n\
    \           print(f\"Subtotal: {subtotal.value} has confidence: {subtotal.confidence}\"\
    )\n       total_tax = invoice.fields.get(\"TotalTax\")\n       if total_tax:\n\
    \           print(\n               f\"Total Tax: {total_tax.value} has confidence:\
    \ {total_tax.confidence}\"\n           )\n       previous_unpaid_balance = invoice.fields.get(\"\
    PreviousUnpaidBalance\")\n       if previous_unpaid_balance:\n           print(\n\
    \               f\"Previous Unpaid Balance: {previous_unpaid_balance.value} has\
    \ confidence: {previous_unpaid_balance.confidence}\"\n           )\n       amount_due\
    \ = invoice.fields.get(\"AmountDue\")\n       if amount_due:\n           print(\n\
    \               f\"Amount Due: {amount_due.value} has confidence: {amount_due.confidence}\"\
    \n           )\n       service_start_date = invoice.fields.get(\"ServiceStartDate\"\
    )\n       if service_start_date:\n           print(\n               f\"Service\
    \ Start Date: {service_start_date.value} has confidence: {service_start_date.confidence}\"\
    \n           )\n       service_end_date = invoice.fields.get(\"ServiceEndDate\"\
    )\n       if service_end_date:\n           print(\n               f\"Service End\
    \ Date: {service_end_date.value} has confidence: {service_end_date.confidence}\"\
    \n           )\n       service_address = invoice.fields.get(\"ServiceAddress\"\
    )\n       if service_address:\n           print(\n               f\"Service Address:\
    \ {service_address.value} has confidence: {service_address.confidence}\"\n   \
    \        )\n       service_address_recipient = invoice.fields.get(\"ServiceAddressRecipient\"\
    )\n       if service_address_recipient:\n           print(\n               f\"\
    Service Address Recipient: {service_address_recipient.value} has confidence: {service_address_recipient.confidence}\"\
    \n           )\n       remittance_address = invoice.fields.get(\"RemittanceAddress\"\
    )\n       if remittance_address:\n           print(\n               f\"Remittance\
    \ Address: {remittance_address.value} has confidence: {remittance_address.confidence}\"\
    \n           )\n       remittance_address_recipient = invoice.fields.get(\"RemittanceAddressRecipient\"\
    )\n       if remittance_address_recipient:\n           print(\n              \
    \ f\"Remittance Address Recipient: {remittance_address_recipient.value} has confidence:\
    \ {remittance_address_recipient.confidence}\"\n           )\n\n   ````\n\nAnalyze\
    \ a custom document. For more samples see the *samples* folder.<!--[!code-python[Main](les\\\
    v3.2_and_later\\sample_analyze_custom_documents.py )]-->\n\n<!-- literal_block\
    \ {\"ids\": [], \"classes\": [], \"names\": [], \"dupnames\": [], \"backrefs\"\
    : [], \"source\": \"C:\\\\hostedtoolcache\\\\windows\\\\Python\\\\3.11.5\\\\x64\\\
    \\Lib\\\\site-packages\\\\py2docfx\\\\dist_temp\\\\5\\\\azure-ai-formrecognizer-3.3.0\\\
    \\samples\\\\v3.2_and_later\\\\sample_analyze_custom_documents.py\", \"xml:space\"\
    : \"preserve\", \"force\": false, \"language\": \"python\", \"highlight_args\"\
    : {\"linenostart\": 1}, \"linenos\": false} -->\n\n````python\n\n   from azure.core.credentials\
    \ import AzureKeyCredential\n   from azure.ai.formrecognizer import DocumentAnalysisClient\n\
    \n   endpoint = os.environ[\"AZURE_FORM_RECOGNIZER_ENDPOINT\"]\n   key = os.environ[\"\
    AZURE_FORM_RECOGNIZER_KEY\"]\n   model_id = os.getenv(\"CUSTOM_BUILT_MODEL_ID\"\
    , custom_model_id)\n\n   document_analysis_client = DocumentAnalysisClient(\n\
    \       endpoint=endpoint, credential=AzureKeyCredential(key)\n   )\n\n   # Make\
    \ sure your document's type is included in the list of document types the custom\
    \ model can analyze\n   with open(path_to_sample_documents, \"rb\") as f:\n  \
    \     poller = document_analysis_client.begin_analyze_document(\n           model_id=model_id,\
    \ document=f\n       )\n   result = poller.result()\n\n   for idx, document in\
    \ enumerate(result.documents):\n       print(f\"--------Analyzing document #{idx\
    \ + 1}--------\")\n       print(f\"Document has type {document.doc_type}\")\n\
    \       print(f\"Document has document type confidence {document.confidence}\"\
    )\n       print(f\"Document was analyzed with model with ID {result.model_id}\"\
    )\n       for name, field in document.fields.items():\n           field_value\
    \ = field.value if field.value else field.content\n           print(\n       \
    \        f\"......found field of type '{field.value_type}' with value '{field_value}'\
    \ and with confidence {field.confidence}\"\n           )\n\n   # iterate over\
    \ tables, lines, and selection marks on each page\n   for page in result.pages:\n\
    \       print(f\"\\nLines found on page {page.page_number}\")\n       for line\
    \ in page.lines:\n           print(f\"...Line '{line.content}'\")\n       for\
    \ word in page.words:\n           print(f\"...Word '{word.content}' has a confidence\
    \ of {word.confidence}\")\n       if page.selection_marks:\n           print(f\"\
    \\nSelection marks found on page {page.page_number}\")\n           for selection_mark\
    \ in page.selection_marks:\n               print(\n                   f\"...Selection\
    \ mark is '{selection_mark.state}' and has a confidence of {selection_mark.confidence}\"\
    \n               )\n\n   for i, table in enumerate(result.tables):\n       print(f\"\
    \\nTable {i + 1} can be found on page:\")\n       for region in table.bounding_regions:\n\
    \           print(f\"...{region.page_number}\")\n       for cell in table.cells:\n\
    \           print(\n               f\"...Cell[{cell.row_index}][{cell.column_index}]\
    \ has text '{cell.content}'\"\n           )\n   print(\"-----------------------------------\"\
    )\n\n   ````\n"
- uid: azure.ai.formrecognizer.DocumentAnalysisClient.begin_analyze_document_from_url
  name: begin_analyze_document_from_url
  summary: 'Analyze field text and semantic values from a given document.

    The input must be the location (URL) of the document to be analyzed.


    New in version 2023-07-31: The *features* keyword argument.'
  signature: 'begin_analyze_document_from_url(model_id: str, document_url: str, **kwargs:
    Any) -> LROPoller[AnalyzeResult]'
  parameters:
  - name: model_id
    description: 'A unique model identifier can be passed in as a string.

      Use this to specify the custom model ID or prebuilt model ID. Prebuilt model
      IDs supported

      can be found here: [https://aka.ms/azsdk/formrecognizer/models](https://aka.ms/azsdk/formrecognizer/models)'
    isRequired: true
    types:
    - <xref:str>
  - name: document_url
    description: 'The URL of the document to analyze. The input must be a valid, properly

      encoded  (i.e. encode special characters, such as empty spaces), and publicly
      accessible URL.

      For service supported file types, see: [https://aka.ms/azsdk/formrecognizer/supportedfiles](https://aka.ms/azsdk/formrecognizer/supportedfiles).'
    isRequired: true
    types:
    - <xref:str>
  - name: pages
    description: 'Custom page numbers for multi-page documents(PDF/TIFF). Input the
      page numbers

      and/or ranges of pages you want to get in the result. For a range of pages,
      use a hyphen, like

      *pages="1-3, 5-6"*. Separate each page number or range with a comma.'
    types:
    - <xref:str>
  - name: locale
    description: 'Locale hint of the input document.

      See supported locales here: [https://aka.ms/azsdk/formrecognizer/supportedlocales](https://aka.ms/azsdk/formrecognizer/supportedlocales).'
    types:
    - <xref:str>
  - name: features
    description: Document analysis features to enable.
    types:
    - <xref:list>[<xref:str>]
  return:
    description: 'An instance of an LROPoller. Call *result()* on the poller

      object to return a <xref:azure.ai.formrecognizer.AnalyzeResult>.'
    types:
    - <xref:azure.core.polling.LROPoller>[<xref:azure.ai.formrecognizer.AnalyzeResult>]
  exceptions:
  - type: azure.core.exceptions.HttpResponseError
  examples:
  - "Analyze a receipt. For more samples see the *samples* folder.<!--[!code-python[Main](les\\\
    v3.2_and_later\\sample_analyze_receipts_from_url.py )]-->\n\n<!-- literal_block\
    \ {\"ids\": [], \"classes\": [], \"names\": [], \"dupnames\": [], \"backrefs\"\
    : [], \"source\": \"C:\\\\hostedtoolcache\\\\windows\\\\Python\\\\3.11.5\\\\x64\\\
    \\Lib\\\\site-packages\\\\py2docfx\\\\dist_temp\\\\5\\\\azure-ai-formrecognizer-3.3.0\\\
    \\samples\\\\v3.2_and_later\\\\sample_analyze_receipts_from_url.py\", \"xml:space\"\
    : \"preserve\", \"force\": false, \"language\": \"python\", \"highlight_args\"\
    : {\"linenostart\": 1}, \"linenos\": false} -->\n\n````python\n\n   from azure.core.credentials\
    \ import AzureKeyCredential\n   from azure.ai.formrecognizer import DocumentAnalysisClient\n\
    \n   endpoint = os.environ[\"AZURE_FORM_RECOGNIZER_ENDPOINT\"]\n   key = os.environ[\"\
    AZURE_FORM_RECOGNIZER_KEY\"]\n\n   document_analysis_client = DocumentAnalysisClient(\n\
    \       endpoint=endpoint, credential=AzureKeyCredential(key)\n   )\n   url =\
    \ \"https://raw.githubusercontent.com/Azure/azure-sdk-for-python/main/sdk/formrecognizer/azure-ai-formrecognizer/tests/sample_forms/receipt/contoso-receipt.png\"\
    \n   poller = document_analysis_client.begin_analyze_document_from_url(\n    \
    \   \"prebuilt-receipt\", document_url=url\n   )\n   receipts = poller.result()\n\
    \n   for idx, receipt in enumerate(receipts.documents):\n       print(f\"--------Analysis\
    \ of receipt #{idx + 1}--------\")\n       print(f\"Receipt type: {receipt.doc_type\
    \ if receipt.doc_type else 'N/A'}\")\n       merchant_name = receipt.fields.get(\"\
    MerchantName\")\n       if merchant_name:\n           print(\n               f\"\
    Merchant Name: {merchant_name.value} has confidence: \"\n               f\"{merchant_name.confidence}\"\
    \n           )\n       transaction_date = receipt.fields.get(\"TransactionDate\"\
    )\n       if transaction_date:\n           print(\n               f\"Transaction\
    \ Date: {transaction_date.value} has confidence: \"\n               f\"{transaction_date.confidence}\"\
    \n           )\n       if receipt.fields.get(\"Items\"):\n           print(\"\
    Receipt items:\")\n           for idx, item in enumerate(receipt.fields.get(\"\
    Items\").value):\n               print(f\"...Item #{idx + 1}\")\n            \
    \   item_description = item.value.get(\"Description\")\n               if item_description:\n\
    \                   print(\n                       f\"......Item Description:\
    \ {item_description.value} has confidence: \"\n                       f\"{item_description.confidence}\"\
    \n                   )\n               item_quantity = item.value.get(\"Quantity\"\
    )\n               if item_quantity:\n                   print(\n             \
    \          f\"......Item Quantity: {item_quantity.value} has confidence: \"\n\
    \                       f\"{item_quantity.confidence}\"\n                   )\n\
    \               item_price = item.value.get(\"Price\")\n               if item_price:\n\
    \                   print(\n                       f\"......Individual Item Price:\
    \ {item_price.value} has confidence: \"\n                       f\"{item_price.confidence}\"\
    \n                   )\n               item_total_price = item.value.get(\"TotalPrice\"\
    )\n               if item_total_price:\n                   print(\n          \
    \             f\"......Total Item Price: {item_total_price.value} has confidence:\
    \ \"\n                       f\"{item_total_price.confidence}\"\n            \
    \       )\n       subtotal = receipt.fields.get(\"Subtotal\")\n       if subtotal:\n\
    \           print(f\"Subtotal: {subtotal.value} has confidence: {subtotal.confidence}\"\
    )\n       tax = receipt.fields.get(\"TotalTax\")\n       if tax:\n           print(f\"\
    Total tax: {tax.value} has confidence: {tax.confidence}\")\n       tip = receipt.fields.get(\"\
    Tip\")\n       if tip:\n           print(f\"Tip: {tip.value} has confidence: {tip.confidence}\"\
    )\n       total = receipt.fields.get(\"Total\")\n       if total:\n          \
    \ print(f\"Total: {total.value} has confidence: {total.confidence}\")\n      \
    \ print(\"--------------------------------------\")\n\n   ````\n"
- uid: azure.ai.formrecognizer.DocumentAnalysisClient.begin_classify_document
  name: begin_classify_document
  summary: 'Classify a document using a document classifier. For more information
    on how to build

    a custom classifier model, see [https://aka.ms/azsdk/formrecognizer/buildclassifiermodel](https://aka.ms/azsdk/formrecognizer/buildclassifiermodel).


    New in version 2023-07-31: The *begin_classify_document* client method.'
  signature: 'begin_classify_document(classifier_id: str, document: bytes | IO[bytes],
    **kwargs: Any) -> LROPoller[AnalyzeResult]'
  parameters:
  - name: classifier_id
    description: A unique document classifier identifier can be passed in as a string.
    isRequired: true
    types:
    - <xref:str>
  - name: document
    description: 'File stream or bytes. For service supported file types, see:

      [https://aka.ms/azsdk/formrecognizer/supportedfiles](https://aka.ms/azsdk/formrecognizer/supportedfiles).'
    isRequired: true
    types:
    - <xref:bytes>
    - <xref:typing.IO>[<xref:bytes>]
  return:
    description: 'An instance of an LROPoller. Call *result()* on the poller

      object to return a <xref:azure.ai.formrecognizer.AnalyzeResult>.'
    types:
    - <xref:azure.core.polling.LROPoller>[<xref:azure.ai.formrecognizer.AnalyzeResult>]
  exceptions:
  - type: azure.core.exceptions.HttpResponseError
  examples:
  - "Classify a document. For more samples see the *samples* folder.<!--[!code-python[Main](les\\\
    v3.2_and_later\\sample_classify_document.py )]-->\n\n<!-- literal_block {\"ids\"\
    : [], \"classes\": [], \"names\": [], \"dupnames\": [], \"backrefs\": [], \"source\"\
    : \"C:\\\\hostedtoolcache\\\\windows\\\\Python\\\\3.11.5\\\\x64\\\\Lib\\\\site-packages\\\
    \\py2docfx\\\\dist_temp\\\\5\\\\azure-ai-formrecognizer-3.3.0\\\\samples\\\\v3.2_and_later\\\
    \\sample_classify_document.py\", \"xml:space\": \"preserve\", \"force\": false,\
    \ \"language\": \"python\", \"highlight_args\": {\"linenostart\": 1}, \"linenos\"\
    : false} -->\n\n````python\n\n   from azure.core.credentials import AzureKeyCredential\n\
    \   from azure.ai.formrecognizer import DocumentAnalysisClient\n\n   endpoint\
    \ = os.environ[\"AZURE_FORM_RECOGNIZER_ENDPOINT\"]\n   key = os.environ[\"AZURE_FORM_RECOGNIZER_KEY\"\
    ]\n   classifier_id = os.getenv(\"CLASSIFIER_ID\", classifier_id)\n\n   document_analysis_client\
    \ = DocumentAnalysisClient(\n       endpoint=endpoint, credential=AzureKeyCredential(key)\n\
    \   )\n   with open(path_to_sample_documents, \"rb\") as f:\n       poller = document_analysis_client.begin_classify_document(\n\
    \           classifier_id, document=f\n       )\n   result = poller.result()\n\
    \n   print(\"----Classified documents----\")\n   for doc in result.documents:\n\
    \       print(\n           f\"Found document of type '{doc.doc_type or 'N/A'}'\
    \ with a confidence of {doc.confidence} contained on \"\n           f\"the following\
    \ pages: {[region.page_number for region in doc.bounding_regions]}\"\n       )\n\
    \n   ````\n"
- uid: azure.ai.formrecognizer.DocumentAnalysisClient.begin_classify_document_from_url
  name: begin_classify_document_from_url
  summary: 'Classify a given document with a document classifier. For more information
    on how to build

    a custom classifier model, see [https://aka.ms/azsdk/formrecognizer/buildclassifiermodel](https://aka.ms/azsdk/formrecognizer/buildclassifiermodel).

    The input must be the location (URL) of the document to be classified.


    New in version 2023-07-31: The *begin_classify_document_from_url* client method.'
  signature: 'begin_classify_document_from_url(classifier_id: str, document_url: str,
    **kwargs: Any) -> LROPoller[AnalyzeResult]'
  parameters:
  - name: classifier_id
    description: A unique document classifier identifier can be passed in as a string.
    isRequired: true
    types:
    - <xref:str>
  - name: document_url
    description: 'The URL of the document to classify. The input must be a valid,
      properly

      encoded  (i.e. encode special characters, such as empty spaces), and publicly
      accessible URL

      of one of the supported formats: [https://aka.ms/azsdk/formrecognizer/supportedfiles](https://aka.ms/azsdk/formrecognizer/supportedfiles).'
    isRequired: true
    types:
    - <xref:str>
  return:
    description: 'An instance of an LROPoller. Call *result()* on the poller

      object to return a <xref:azure.ai.formrecognizer.AnalyzeResult>.'
    types:
    - <xref:azure.core.polling.LROPoller>[<xref:azure.ai.formrecognizer.AnalyzeResult>]
  exceptions:
  - type: azure.core.exceptions.HttpResponseError
  examples:
  - "Classify a document. For more samples see the *samples* folder.<!--[!code-python[Main](les\\\
    v3.2_and_later\\sample_classify_document_from_url.py )]-->\n\n<!-- literal_block\
    \ {\"ids\": [], \"classes\": [], \"names\": [], \"dupnames\": [], \"backrefs\"\
    : [], \"source\": \"C:\\\\hostedtoolcache\\\\windows\\\\Python\\\\3.11.5\\\\x64\\\
    \\Lib\\\\site-packages\\\\py2docfx\\\\dist_temp\\\\5\\\\azure-ai-formrecognizer-3.3.0\\\
    \\samples\\\\v3.2_and_later\\\\sample_classify_document_from_url.py\", \"xml:space\"\
    : \"preserve\", \"force\": false, \"language\": \"python\", \"highlight_args\"\
    : {\"linenostart\": 1}, \"linenos\": false} -->\n\n````python\n\n   from azure.core.credentials\
    \ import AzureKeyCredential\n   from azure.ai.formrecognizer import DocumentAnalysisClient\n\
    \n   endpoint = os.environ[\"AZURE_FORM_RECOGNIZER_ENDPOINT\"]\n   key = os.environ[\"\
    AZURE_FORM_RECOGNIZER_KEY\"]\n   classifier_id = os.getenv(\"CLASSIFIER_ID\",\
    \ classifier_id)\n\n   document_analysis_client = DocumentAnalysisClient(\n  \
    \     endpoint=endpoint, credential=AzureKeyCredential(key)\n   )\n\n   url =\
    \ \"https://raw.githubusercontent.com/Azure/azure-sdk-for-python/main/sdk/formrecognizer/azure-ai-formrecognizer/tests/sample_forms/forms/IRS-1040.pdf\"\
    \n\n   poller = document_analysis_client.begin_classify_document_from_url(\n \
    \      classifier_id, document_url=url\n   )\n   result = poller.result()\n\n\
    \   print(\"----Classified documents----\")\n   for doc in result.documents:\n\
    \       print(\n           f\"Found document of type '{doc.doc_type or 'N/A'}'\
    \ with a confidence of {doc.confidence} contained on \"\n           f\"the following\
    \ pages: {[region.page_number for region in doc.bounding_regions]}\"\n       )\n\
    \n   ````\n"
- uid: azure.ai.formrecognizer.DocumentAnalysisClient.close
  name: close
  summary: Close the <xref:azure.ai.formrecognizer.DocumentAnalysisClient> session.
  signature: close() -> None